Modeling of Soil Water Erosion: A Comparison of Empirical and Physical Approaches in Mexico

Abstract

Soil erosion is a pressing environmental issue, accelerated by agricultural practices and climate variability, and it poses significant challenges to land productivity and water quality. This thesis investigates soil erosion processes and sediment yield modeling at both hillslope and watershed scales in an arid region of north-central Mexico, using empirical and physical modeling approaches to guide conservation strategies. Three comprehensive studies were undertaken to assess the impact of tillage practices, soil moisture conditions, and the appropriateness of models for estimating erosion. The first study assessed the impacts of tillage systems and antecedent soil moisture conditions on erosion and runoff under high intensity simulated rainfall. The findings demonstrated that conservation-oriented practices, such as crop residue cover and no-till methods, effectively mitigate erosion and runoff, particularly in conditions characterized by dry soil. The subsequent study compared the Revised Universal Soil Loss Equation (RUSLE) and the Water Erosion Prediction Project (WEPP) models to ascertain the most efficacious approach for predicting erosion on agricultural hillslopes. RUSLE exhibited superior performance compared to WEPP in capturing erosion trends across various treatments, indicating its appropriateness for regional conditions; however, WEPP yielded valuable insights in specific scenarios involving conventional tillage. The last study expanded the modeling of sediment yield to encompass the watershed scale by employing the Modified Universal Soil Loss Equation (MUSLE) with its parameters sourced from hillslope assessments. An approach utilizing daily water balance, which integrates Actual Evapotranspiration (AET), enabled the model to account for variations in soil moisture, thereby elucidating a nonlinear association between precipitation and sediment yield. This association demonstrated that sediment yield initially increases to a maximum before attenuating during episodes of extreme rainfall. Despite MUSLE's capability to accurately reflect sediment dynamics, it exhibited a tendency to overestimate sediment yield in the context of intense rainfall events, underscoring the necessity for advanced modeling approaches in semi-arid regions. This research advances erosion modeling by demonstrating the importance of context-specific model calibration, conservation practices, and the integration of soil moisture dynamics to improve sediment yield predictions. These findings offer practical insights for soil and water conservation in semi-arid environments and contribute valuable data to guide erosion management in similar landscapes.